Article

Genetics-driven Risk Predictions with Differentiable Mendelian Randomization

2024-03-11

Abstract excerpt

Accurate predictive models of future disease onset are crucial for effective preventive healthcare, yet longitudinal datasets linking early risk factors to subsequent health outcomes are scarce. To address this challenge, we introduce Differentiable Mendelian Randomization (DMR), an extension of the classical Mendelian Randomization framework to learn risk predictors without longitudinal data. To do so, DMR levera...

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Literature Corpus work: 3a5b9590-b03b-5ac6-a117-a60346bf7058
DOI: 10.1101/2024.03.06.583727

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